Twitter Mining for Discovery, Prediction and Causality: Applications and Methodologies

Daniel O'Leary

Intelligent Systems in Accounting, Finance and Management, 2015, vol. 22, issue 3, 227-247

Abstract: Twitter has found substantial use in a number of settings. For example, Twitter played a major role in the ‘Arab Spring’ and has been adopted by a large number of the Fortune 100. All of these and other events have led to a large database of Twitter tweets that has attracted the attention of a number of companies and researchers through what has become known as ‘Twitter mining’ (also known as ‘TwitterMining’). This paper analyses some of the approaches used to gather information and knowledge from Twitter for Twitter mining. In addition, this paper reviews a number of the applications that employ Twitter Mining, investigating Twitter information for prediction, discovery and as an informational basis of causation. Copyright © 2015 John Wiley & Sons, Ltd.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1002/isaf.1376

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:isacfm:v:22:y:2015:i:3:p:227-247

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1099-1174

Access Statistics for this article

More articles in Intelligent Systems in Accounting, Finance and Management from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().